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Modeling the transport of organic chemicals between polyethylene passive samplers and water in finite and infinite bath conditions

Author:
Tcaciuc, A. Patricia, Apell, Jennifer N., Gschwend, Philip M.
Source:
Environmental toxicology and chemistry 2015 v.34 no.12 pp. 2739-2749
ISSN:
0730-7268
Subject:
DDT (pesticide), diffusivity, mathematical models, monitoring, partition coefficients, phenols, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, polyethylene, samplers, sorption, surface water, turbulent flow
Abstract:
Understanding the transfer of chemicals between passive samplers and water is essential for their use as monitoring devices of organic contaminants in surface waters. By applying Fick's second law to diffusion through the polymer and an aqueous boundary layer, the authors derived a mathematical model for the uptake of chemicals into a passive sampler from water, in finite and infinite bath conditions. The finite bath model performed well when applied to laboratory observations of sorption into polyethylene (PE) sheets for various chemicals (polycyclic aromatic hydrocarbons, polychlorinated biphenyls [PCBs], and dichlorodiphenyltrichloroethane [DDT]) and at varying turbulence levels. The authors used the infinite bath model to infer fractional equilibration of PCB and DDT analytes in field‐deployed PE, and the results were nearly identical to those obtained using the sampling rate model. However, further comparison of the model and the sampling rate model revealed that the exchange of chemicals was inconsistent with the sampling rate model for partially or fully membrane‐controlled transfer, which would be expected in turbulent conditions or when targeting compounds with small polymer diffusivities and small partition coefficients (e.g., phenols, some pesticides, and others). The model can be applied to other polymers besides PE as well as other chemicals and in any transfer regime (membrane, mixed, or water boundary layer–controlled). Lastly, the authors illustrate practical applications of this model such as improving passive sampler design and understanding the kinetics of passive dosing experiments. Environ Toxicol Chem 2015;34:2739–2749. © 2015 SETAC
Agid:
4666185